Interested in this AI Agent Developer role at Preferred Business Systems, Inc.?
Apply Now →Skills & Technologies
About This Role
Description:
About Us
Preferred Business Systems (PBS) has been making technology simple for small and midsize businesses since 1997. From our headquarters in Whippany, New Jersey, we deliver managed IT, cybersecurity, cloud, business communications, and office technology to organizations across New Jersey, New York, Pennsylvania, Connecticut, and the rest of the U.S.
Our clients span healthcare, law, logistics, warehousing, manufacturing, construction, hospitality, and financial services. Our growing AI and Automation team builds AI-powered agents that take repetitive and complex work off their plates, from executive assistance and recruiting to warehouse dispatching and customer communications.
The Role
As an AI Agent Developer, you'll design, build, integrate, and maintain AI agents that streamline real business operations. You'll work within the architecture and standards set by technical leadership, owning the implementation details that turn an approved design into a working solution.
You'll partner with Business Strategists, who lead customer relationships and define requirements. Your job is to turn those requirements into automations that are functional, reliable, and secure.
Prior AI agent experience is a plus but not required. If you have a strong foundation in software development, APIs, and automation, we'll help you grow into the AI side.
What You'll Do
Build and integrate AI agents
- Develop AI agents using Microsoft Copilot Studio, Power Automate, Azure services, and custom code.
- Build custom applications and integrations in Python, TypeScript, or similar languages.
- Connect agents to Microsoft 365, Microsoft Graph, third-party APIs, databases, and customer business applications.
- Implement LLM-powered workflows, tool calling, conditional logic, and human approval steps.
- Manage LLM usage costs and performance as part of every build.
- Create reusable components that speed up future implementations.
Work with customers
- Join Business Strategists in technical discovery to identify integration needs and system limitations.
- Support customer demos, solution testing, and troubleshooting.
- Keep internal stakeholders informed on progress, challenges, and risks.
Test, deploy, and improve
- Write and run functional, integration, and error-handling tests.
- Evaluate LLM output quality, including consistency, hallucinations, and edge cases.
- Validate accuracy, permissions, and reliability before deployment.
- Deploy approved solutions into customer environments.
- Resolve escalated defects and improve agents based on performance data and customer feedback.
Build securely and responsibly
- Implement secure authentication, authorization, and least-privilege access.
- Protect customer data and credentials using approved practices.
- Identify risks such as sensitive data exposure, prompt injection, and unauthorized actions.
- Build in human approval checkpoints and audit logging.
- Participate in security reviews and remediate findings.
Document and hand off
- Maintain documentation for agents, integrations, configurations, and deployments.
- Write troubleshooting guides and support runbooks.
- Define monitoring, alerting, and logging requirements.
- Train our support team so every deployed agent is supportable long-term.
Requirements:
What You Bring
- 2+ years of professional software or automation development experience.
- Proficiency in Python, TypeScript, or a comparable language, using Git and standard development practices.
- Experience building and consuming REST APIs and integrating with third-party systems.
- Solid understanding of OAuth 2.0, authorization, and secure credential handling.
- Familiarity with Microsoft 365 and Power Automate (or a comparable workflow platform).
- Strong debugging and problem-solving skills.
- Clear communication with both technical and nontechnical people.
Nice to Have
- Experience building AI agents or LLM-powered applications.
- Familiarity with Microsoft Copilot Studio, Microsoft Graph API, and Azure services.
- Understanding of LLM APIs, function calling, and agent orchestration.
- Familiarity with retrieval-augmented generation (RAG) and vector databases.
- Experience with AI evaluation, monitoring, and observability.
- SQL and data integration experience.
- Experience in an MSP or multi-customer environment.
- Familiarity with CI/CD pipelines and cloud deployments.
Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 9,079 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Preferred Business Systems, Inc., this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $215,000 based on 203 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Preferred Business Systems, Inc. AI Hiring
Preferred Business Systems, Inc. has 1 open AI role right now. They're hiring across AI Agent Developer. Based in Whippany, NJ, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.